This invention relates generally to medical imaging systems, and more particularly, to providing multiple volume renderings from the same data set acquired by a medical imaging system.
Medical imaging systems are used in different applications to image different regions or areas (e.g., different organs) of patients. For example, ultrasound imaging may be used to generate images of a heart. These images are then displayed for review and analysis by a user. The images also may be modified or adjusted to better view or visualize different regions or objects of interest.
Visualization by volume rendering is a known technique to produce realistic images (e.g., three-dimensional images) based on a three-dimensional data set. For example, three-dimensional data may be projected onto a two-dimensional image in a given viewing direction. The projection can be performed using known algorithms, for example, using ray-tracing algorithms and advanced lighting models. A user is typically able to adjust the view direction for the image such that, for example, an imaged object may be viewed from different angles or perspectives. For example, a user can move an ultrasound probe in different directions and angles to acquire and view images of a heart at different locations around the heart. A user also may manipulate stored data to generate different views.
In volume imaging, another important functionality is the ability to crop parts of the imaged object in order to look inside the object. The crop function can be performed in different ways. Cropping is commonly performed by defining a plane that cuts into the imaged object and the part of the object on one side of that plane is removed from the rendering.
When visualizing objects using volume imaging challenges arise. For example, a challenge with visualization of the human heart using volume ultrasound is to navigate in the volumetric data and identify anatomical structures from different angles in order to produce clinically relevant views. Typically, an operator manually defines single rendering views by cutting the volume at random locations with no relation to other previously defined views. For example, an operator generates one view of a heart by cropping the image to generate a single view and then rotating and/or translating the image to another view and then cropping the image again at another location to generate another view. This process is repeated until multiple different images defining different views are generated.
Thus, the manual process to define and generate different views of an image is tedious and time consuming. Additionally, the views generated may not capture the entire region or regions of interest from different perspectives, thereby potentially resulting in excluding clinically relevant portions of the image and possible improper diagnosis.